Recently, researchers introduce neural networks to generate code in a general-purpose programming language. [1]} ling2016latent adopt a sequence-to-sequence model, but enhance it with multiple predictors. Other studies generate programs along abstract syntax trees [2]}, [3]}, [4]}. However, their decoders are all based on RNNs, which are shown improper for code generation in our experiments.
